Fe@χ3-borophene as a promising catalyst for CO oxidation reaction: A first-principles study.

A novel single-atom catalyst of Fe adsorbed on χ3-borophene has been proposed as a potential catalyst for CO oxidation reaction (COOR). Quantitative pictures have been provided of both the stability of Fe@χ3-borophene and various kinetic reaction pathways using first-principles calculations. Strong adsorption energy of -3.19 eV and large diffusion potential of 3.51 eV indicates that Fe@χ3-borophene is highly stable. By exploring reaction mechanisms for COOR, both Eley-Ridel (E-R) and trimolecule E-R (TER) were identified as possible reaction paths. Low reaction barriers with 0.49 eV of E-R and 0.57 eV of TER suggest that Fe@χ3-borophene is a very promising catalyst for COOR. Charge transfer between the χ3-borophene and CO, O2 and CO2 gas molecules plays a key role in lowering the energy barrier during the reactions. Our results propose that Fe@χ3-borophene can be a good candidate of single-atom catalyst for COOR with both high stability and catalytic activity.

Neural networks-based variationally enhanced sampling.

Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method [O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.

Improving collective variables: The case of crystallization.

Several enhanced sampling methods, such as umbrella sampling or metadynamics, rely on the identification of an appropriate set of collective variables. Recently two methods have been proposed to alleviate the task of determining efficient collective variables. One is based on linear discriminant analysis; the other is based on a variational approach to conformational dynamics and uses time-lagged independent component analysis. In this paper, we compare the performance of these two approaches in the study of the homogeneous crystallization of two simple metals. We focus on Na and Al and search for the most efficient collective variables that can be expressed as a linear combination of X-ray diffraction peak intensities. We find that the performances of the two methods are very similar. Wherever the different metastable states are well-separated, the method based on linear discriminant analysis, based on its harmonic version, is to be preferred because simpler to implement and less computationally demanding. The variational approach, however, has the potential to discover the existence of different metastable states.

What are grain boundary structures in graphene?

We have developed a new global optimization method for the determination of the interface structure based on the differential evolution algorithm. Here, we applied this method to search for the ground state atomic structures of the grain boundary (GB) between armchair and zigzag oriented graphene. We find two new grain boundary structures with a considerably lower formation energy of about 1 eV nm(-1) than those of the previously widely used structural models. We also systematically investigate the symmetric GBs with the GB angle ranging from 0° to 60°, and find some new GB structures. Surprisingly, for an intermediate GB angle, the formation energy does not depend monotonically on the defect concentration. We also discovered an interesting linear relationship between the GB density and the GB angle. Our new method provides an important novel route for the determination of GB structures and other interface structures, and our comprehensive study on GB structures could provide new structural information and guidelines to this area.

Simultaneous etching and doping of TiO2 nanowire arrays for enhanced photoelectrochemical performance.

We developed a postgrowth doping method of TiO2 nanowire arrays by a simultaneous hydrothermal etching and doping in a weakly alkaline condition. The obtained tungsten-doped TiO2 core-shell nanowires have an amorphous shell with a rough surface, in which W species are incorporated into the amorphous TiO2 shell during this simultaneous etching/regrowth step for the optimization of photoelectrochemical performance. Photoanodes made of these W-doped TiO2 core-shell nanowires show a much enhanced photocurrent density of ~1.53 mA/cm(2) at 0.23 V vs Ag/AgCl (1.23 V vs reversible hydrogen electrode), almost 225% of that of the pristine TiO2 nanowire photoanodes. The electrochemical impedance spectroscopy measurement and the density functional theory calculation demonstrate that the substantially improved performance of the dual W-doped and etched TiO2 nanowires is attributed to the enhancement of charge transfer and the increase of charge carrier density, resulting from the combination effect of etching and W-doping. This unconventional, simultaneous etching and doping of pregrown nanowires is facile and takes place under moderate conditions, and it may be extended for other dopants and host materials with increased photoelectrochemical performances.

Prediction of (TiO2)x(Cu2O)y alloys for efficient photoelectrochemical water splitting.

The formation of (TiO(2))(x)(Cu(2)O)(y) solid-solutions is investigated using a global optimization evolutionary algorithm. First-principles calculations based on density functional theory are then used to gain insight into the electronic properties of these alloys. We find that: (i) Ti and Cu in (TiO(2))(x)(Cu(2)O)(y) alloys have similar local environments as in bulk TiO(2) and Cu(2)O except for (TiO(2))(Cu(2)O) which has some trigonal-planar Cu ions. (ii) The predicted optical band gaps are around 2.1 eV (590 nm), thus having much better performance in the absorption of visible light compared with both binary oxides. (iii) (TiO(2))(2)(Cu(2)O) has the lowest formation energy amongst all studied alloys and the positions of its band edges are found to be suitable for solar-driven water splitting applications.